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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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@githubtrending · Post #15478 · 02/07/2026, 01:30 PM

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#python#agent_skills#ai_agents#antigravity#automation#claude#claude_code#codex#composio#cursor#gemini_cli#mcp#rube#saas#skill#workflow_automation Claude Skills are customizable workflows that boost productivity on Claude.ai, Claude Code, and API by handling tasks like document editing, code development, data analysis, app automation (emails, Slack, GitHub via Composio's 500+ integrations), and more. Install the connect-apps plugin, add your free Composio API key, and restart to enable real actions across 1000+ apps. This saves time, automates repetitive work, and lets you focus on high-value tasks for faster, consistent results everywhere you use Claude. https://github.com/ComposioHQ/awesome-claude-skills

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